Special Issue "Sensing Technology for Flood Monitoring and Forecasting"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (31 March 2021) | Viewed by 4887

Special Issue Editors

Department of Geosciences, University of Oslo, N-0316 Oslo, Norway
Interests: hydrological modeling; flood forecasting, regionalization; uncertainty; impact of climate change and land use change; evapotranspiration
Special Issues, Collections and Topics in MDPI journals
State Key Laboratory of Water Resources and Hydropower Engineering Science, Wuhan University, Wuhan 430072, China
Interests: image recognition; radar technology; hydrology monitoring; hydrology simulation; artificial intelligence; remote sensing
Special Issues, Collections and Topics in MDPI journals
State Key Laboratory of Hydrology-Water Resources and Hydraulics Engineering, Hohai University, Nanjing 210098, China
Interests: remote sensing and GIS applications; hydrological modeling; statistical downscaling; climate change and land use/land cover change impact on water resources
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, with the rapid development of information technology, more and more emerging technologies have been applied in water resource management, such as remote sensing (RS), Artificial Intelligence (AI), the Internet of Things (IoT), intelligent image recognition, etc. These technologies can be directly applied to the monitoring of hydrological variables and can also be indirectly applied to hydrological modeling, providing technical support for flood forecasting and warning in a basin. RS technology can be applied to rainfall observation to obtain the continuous spatial distribution of rainfall, such as TRMM and GPM satellites, and it can also be used to monitor the changing of soil moisture, glaciers, lake water body, and flood inundation, which greatly enrich the traditional means of hydrological observation. IoT technology provides new technical means for data collection and transmission, which overcomes the difficulty of data acquisition in some remote areas. Image recognition technologies are also widely used in water level and flow velocity monitoring, such as particle image velocimetry (PIV) and space–time image velocimetry (STIV), which provide new technical means for quickly obtaining water level and flow data. These sensing technologies greatly enrich the ways for flood forecasting and early warning and also provide strong technical support for improving the accuracy of flood forecasting.

Therefore, this Special Issue is aimed at representing the latest advances on current efforts to aid advancing flood monitoring and management through new sensing technologies. We welcome contributions in all fields of remote sensing, flood modeling, flood monitoring, including new systems, signal processing algorithms, as well as new applications. Those include but are not limited to:

RS and GIS in flood forecasting

Flood monitoring and mapping

Flood inundation modelling

Multiple satellite precipitation estimation

The IoT applied in flood monitoring

Spatial data downscaling and assimilation

Image recognition technologies

Particle image velocimetry (PIV)

Space–time image velocimetry (STIV)

AI in flooding forecasting and warning

You may choose our Joint Special Issue in Sensors.

Prof. Dr. Chong-Yu Xu
Prof. Dr. Hua Chen
Prof. Dr. Zengxin Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (1 paper)

Order results
Result details
Select all
Export citation of selected articles as:


19 pages, 4708 KiB  
Flood Hazard Assessment for the Tori Levee Breach of the Indus River Basin, Pakistan
Water 2021, 13(5), 604; https://doi.org/10.3390/w13050604 - 25 Feb 2021
Cited by 12 | Viewed by 4458
Levee breaches are some of the most common hazards in the world and cause the loss of lives, livelihoods, and property destruction. During the 2010 flood in Pakistan, the most devastating breach occurred at Tori Levee on the right bank of the Indus [...] Read more.
Levee breaches are some of the most common hazards in the world and cause the loss of lives, livelihoods, and property destruction. During the 2010 flood in Pakistan, the most devastating breach occurred at Tori Levee on the right bank of the Indus River, downstream of the Guddu Barrage, which caused residual floods in northern Sindh and the adjoining regions of the Balochistan province. In this study, 2D unsteady flow modeling performed for Tori Levee breach computed residual flood inundation by coupling a HEC-RAS (Hydrological Engineering Centre—River Analysis System) 2D hydraulic model with remote sensing and Geographic Information System techniques. The model performance was judged by comparing the observed and simulated water levels (stage) during peak flow at seven different gauging stations located within the Indus River reach and daily flood extents and multi-day composites. The quantitative values for the calibration and validation of the HEC-RAS model showed good performance with a range of difference from 0.13 to −0.54 m between the simulated and observed water levels (stage), 84% match for the maximum flood inundation area, and 73.2% for the measure of fit. The overall averages of these values for the daily flood comparison were 57.12 and 75%, respectively. Furthermore, the simulated maximum flow passed through the Tori Levee breach, which was found to be 4994.47 cumecs (about 15% of peak flow) with a head water stage of 71.56 m. By using the simulated flows through the Tori Levee breach, the flood risk maps for the 2010 flood identified hazard zones according to the flood characteristics (depth, velocity, depth times velocity, arrival time, and duration). All the flood risk maps concluded the fact that the active flood plain was uninhabitable under flood conditions. Full article
(This article belongs to the Special Issue Sensing Technology for Flood Monitoring and Forecasting)
Show Figures

Graphical abstract

Back to TopTop